تجاوز إلى المحتوى الرئيسي
User Image

Achraf El Allali

Assistant Professor

Faculty

علوم الحاسب والمعلومات
Building 31, 2nd floor, room 2119
المنشورات
مقال فى مجلة
2019

Biomolecular databases and subnetwork identification approaches of interest to Big Data community: An Expert Review

Next-generation sequencing approaches and genome-wide studies have become essential for characterizing the mechanisms of human diseases. Consequently, many researchers have applied these approaches to discover the genetic/genomic causes of common complex and rare human diseases, generating multiomics big data that span the continuum of genomics, proteomics, metabolomics, and many other system science fields. Therefore, there is a significant and unmet need for biological databases and tools that enable and empower the researchers to analyze, integrate, and make sense of big data. There are currently large number of databases that offer different types of biological information. In particular, the integration of gene expression profiles and protein–protein interaction networks provides a deeper understanding of the complex multilayered molecular architecture of human diseases. Therefore, there has been a growing interest in developing methodologies that integrate and contextualize big data from molecular interaction networks to identify biomarkers of human diseases at a subnetwork resolution as well. In this expert review, we provide a comprehensive summary of most popular biomolecular databases for molecular interactions (e.g., Biological General Repository for Interaction Datasets, Kyoto Encyclopedia of Genes and Genomes and Search Tool for The Retrieval of Interacting Genes/Proteins), gene–disease associations (e.g., Online Mendelian Inheritance in Man, Disease-Gene Network, MalaCards), and population-specific databases (e.g., Human Genetic Variation Database), and describe some examples of their usage and potential applications. We also present the most recent subnetwork identification approaches and discuss their main advantages and limitations. As the field of data science continues to emerge, the present analysis offers a deeper and contextualized understanding of the available databases in molecular biomedicine.

نوع عمل المنشور
Review
رقم المجلد
23
رقم الانشاء
3
مجلة/صحيفة
OMICS: A Journal of Integrative Biology
مزيد من المنشورات
publications

Next-generation sequencing approaches and genome-wide studies have become essential for characterizing the mechanisms of human diseases.

2019
publications

The development of next-generation sequencing facilitates the study of metagenomics. Computational gene prediction aims to find the location of genes in a given DNA sequence. Gene prediction in…

بواسطة Achraf El Allali
2019
publications

Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs…

2018